THE RELATIONSHIP BETWEEN VEGETATION INDEX AND RICE GROWTH AND RICE YIELD COMPONENTS

doi:10.6046/gtzyyg.1996.01.10

Download: PDF(187 KB)
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

This paper introduces the reletionship between rice production and paddy field spectrum data, it indiCates that:Before rice full-head emergence, the correlation coefficient between ratio vegetation index(RVI)and rice growth (Leafarea index or dry biomass) is extremely high, and a good numerical measurement relation exists between them.After this stage, the correlation coefficient between RVI and dry biomass is remarkable.The correlation coefficient between PVI (standardded perpendicular vegrtation index )and rice yield components (ear numbers per Mu, full grainumbers per ear and the weights of one thousand grains) as well as theoretical rice yield are extremely high. Between them there is a good numerical measurement relation.

Keywords Radioactive transfer model Surface scattering Volume scattering Snow

Issue Date: 02 August 2011

	Service

	E-mail this article
	E-mail Alert
	RSS
	Articles by authors

	WU Sheng-Li
	WANG Jian-Ming
	LIU Wei
	YU Qin
	LI Xiao-Chang

Cite this article:

WU Sheng-Li,WANG Jian-Ming,LIU Wei, et al. THE RELATIONSHIP BETWEEN VEGETATION INDEX AND RICE GROWTH AND RICE YIELD COMPONENTS[J]. REMOTE SENSING FOR LAND & RESOURCES, 1996, 8(1): 56-59.

URL:

https://www.gtzyyg.com/EN/10.6046/gtzyyg.1996.01.10 OR https://www.gtzyyg.com/EN/Y1996/V8/I1/56

[1]	XU Yun, XU Aiwen. Classification and detection of cloud, snow and fog in remote sensing images based on random forest[J]. Remote Sensing for Land & Resources, 2021, 33(1): 96-101.
[2]	Xuecheng WANG, Fei YANG, Xing GAO, Yinghui ZHANG. Assessment of forest damage due to ice-snow disaster based on the method of threshold ratio:A case study of Hunan Province[J]. Remote Sensing for Land & Resources, 2018, 30(3): 196-203.
[3]	Ying WU, Sulin JIANG, Zhenhui WANG. Comparison and analysis of the interference identification methods for microwave measurements over snow land[J]. Remote Sensing for Land & Resources, 2018, 30(3): 40-47.
[4]	Xiaogang HOU, Zhaojun ZHENG, Shuai LI, Xuehua CHEN, Yu CUI. Generation of daily cloudless snow cover product in the past 15 years in Xinjiang and accuracy validation[J]. Remote Sensing for Land & Resources, 2018, 30(2): 214-222.
[5]	Haiyang PANG, Xiangsheng KONG, Lili WANG, Yonggang QIAN. A study of the extraction of snow cover using nonlinear ENDSI model[J]. Remote Sensing for Land & Resources, 2018, 30(1): 63-71.
[6]	CHU Duo, DA Wa, LABA Zhuoma, XU Weixin, ZHANG Juan. An analysis of spatial-temporal distribution features of snow cover over the Tibetan Plateau based on MODIS data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(2): 117-124.
[7]	HE Lian, QIN Qiming, REN Huazhong. An adaptive hybrid Freeman/Eigenvalue polarimetric decomposition model[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(2): 8-14.
[8]	YAN Yunpeng, LIU Gang, LIU Jianyu, HAN Cong, ZHAO Zixian. Snow cover remote sensing monitoring in the west of Ngari area in northern Tibet from 2013 to 2014[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(4): 185-190.
[9]	YAN Fuli, XU Jianguo, LU Zhihong. Characteristics of multi-exposure images of BJ-1 intelligent micro satellite and its applications to snow cover extraction[J]. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(1): 28-34.
[10]	MA Liyun, LI Jiangang, LI Shuai. Snowmelt flood disaster monitoring based on FY-3/MERSI in Xinjiang[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(4): 73-78.
[11]	XU Jianhui, SHU Hong, LI Yang. Mapping of monthly mean snow depth in Northern Xinjiang using a multivariate nonlinear regression Kriging model based on MODIS snow cover data[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(3): 84-91.
[12]	SUN Zhiwen, YU Pengshan, XIA Lang, WU Shengli, JIANG Lingmei, GUO Lei. Progress in study of snow parameter inversion by passive microwave remote sensing[J]. REMOTE SENSING FOR LAND & RESOURCES, 2015, 27(1): 9-15.
[13]	BAI Shuying, SHI Jianqiao, SHEN Weishou, GAO Jixi, WANG Guanjun. Spatial-temporal variation of snow depth in Tibet and its response to climatic change in the past 30 years[J]. REMOTE SENSING FOR LAND & RESOURCES, 2014, 26(1): 144-151.
[14]	LI Guanghui, WANG Cheng, XI Xiaohuan, ZHENG Zhaojun, LUO Shezhou, YUE Cairong. Extraction of glacier snowline based on airborne LiDAR and hyperspectral data fusion[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(3): 79-84.
[15]	CHEN Ting, WANG Aihua, WANG Zhiyong. Recognition of ice or snow for panchromatic remote sensing image based on transition region feature[J]. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(2): 27-32.